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Gianazza E, Brioschi M, Eligini S, Banfi C. Mass spectrometry for the study of adipocyte cell secretome in cardiovascular diseases. MASS SPECTROMETRY REVIEWS 2022:e21812. [PMID: 36161723 DOI: 10.1002/mas.21812] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 08/04/2022] [Accepted: 09/03/2022] [Indexed: 06/16/2023]
Abstract
Adipose tissue is classically considered the primary site of lipid storage, but in recent years has garnered appreciation for its broad role as an endocrine organ, capable of remotely signaling to other tissues to alter their metabolic program. The adipose tissue is now recognized as a crucial regulator of cardiovascular health, mediated by the secretion of several bioactive products, with a wide range of endocrine and paracrine effects on the cardiovascular system. Thanks to the development and improvement of high-throughput mass spectrometry, the size and components of the human secretome have been characterized. In this review, we summarized the recent advances in mass spectrometry-based studies of the cell and tissue secretome for the understanding of adipose tissue biology, which may help to decipher the complex molecular mechanisms controlling the crosstalk between the adipose tissue and the cardiovascular system, and their possible clinical translation.
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Affiliation(s)
- Erica Gianazza
- Centro Cardiologico Monzino IRCCS, Unit of Functional Proteomics, Metabolomics and Network Analysis, Milan, Italy
| | - Maura Brioschi
- Centro Cardiologico Monzino IRCCS, Unit of Functional Proteomics, Metabolomics and Network Analysis, Milan, Italy
| | - Sonia Eligini
- Centro Cardiologico Monzino IRCCS, Unit of Functional Proteomics, Metabolomics and Network Analysis, Milan, Italy
| | - Cristina Banfi
- Centro Cardiologico Monzino IRCCS, Unit of Functional Proteomics, Metabolomics and Network Analysis, Milan, Italy
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2
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Zhou B, Ho SS, Greer SU, Spies N, Bell JM, Zhang X, Zhu X, Arthur JG, Byeon S, Pattni R, Saha I, Huang Y, Song G, Perrin D, Wong WH, Ji HP, Abyzov A, Urban AE. Haplotype-resolved and integrated genome analysis of the cancer cell line HepG2. Nucleic Acids Res 2019; 47:3846-3861. [PMID: 30864654 PMCID: PMC6486628 DOI: 10.1093/nar/gkz169] [Citation(s) in RCA: 170] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2018] [Revised: 02/19/2019] [Accepted: 03/01/2019] [Indexed: 12/19/2022] Open
Abstract
HepG2 is one of the most widely used human cancer cell lines in biomedical research and one of the main cell lines of ENCODE. Although the functional genomic and epigenomic characteristics of HepG2 are extensively studied, its genome sequence has never been comprehensively analyzed and higher order genomic structural features are largely unknown. The high degree of aneuploidy in HepG2 renders traditional genome variant analysis methods challenging and partially ineffective. Correct and complete interpretation of the extensive functional genomics data from HepG2 requires an understanding of the cell line’s genome sequence and genome structure. Using a variety of sequencing and analysis methods, we identified a wide spectrum of genome characteristics in HepG2: copy numbers of chromosomal segments at high resolution, SNVs and Indels (corrected for aneuploidy), regions with loss of heterozygosity, phased haplotypes extending to entire chromosome arms, retrotransposon insertions and structural variants (SVs) including complex and somatic genomic rearrangements. A large number of SVs were phased, sequence assembled and experimentally validated. We re-analyzed published HepG2 datasets for allele-specific expression and DNA methylation and assembled an allele-specific CRISPR/Cas9 targeting map. We demonstrate how deeper insights into genomic regulatory complexity are gained by adopting a genome-integrated framework.
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Affiliation(s)
- Bo Zhou
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA.,Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Steve S Ho
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA.,Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Stephanie U Greer
- Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Noah Spies
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.,Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305, USA.,Genome-scale Measurements Group, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA
| | - John M Bell
- Stanford Genome Technology Center, Stanford University, Palo Alto, CA 94304, USA
| | - Xianglong Zhang
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA.,Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Xiaowei Zhu
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA.,Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Joseph G Arthur
- Department of Statistics, Stanford University, Stanford, CA 94305, USA
| | - Seunggyu Byeon
- School of Computer Science and Engineering, College of Engineering, Pusan National University, Busan 46241, South Korea
| | - Reenal Pattni
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA.,Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Ishan Saha
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Yiling Huang
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA.,Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Giltae Song
- School of Computer Science and Engineering, College of Engineering, Pusan National University, Busan 46241, South Korea
| | - Dimitri Perrin
- Science and Engineering Faculty, Queensland University of Technology, Brisbane, QLD 4001, Australia
| | - Wing H Wong
- Department of Statistics, Stanford University, Stanford, CA 94305, USA.,Department of Biomedical Data Science, Bio-X Program, Stanford University, Stanford, CA 94305, USA
| | - Hanlee P Ji
- Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.,Stanford Genome Technology Center, Stanford University, Palo Alto, CA 94304, USA
| | - Alexej Abyzov
- Department of Health Sciences Research, Center for Individualized Medicine, Mayo Clinic, Rochester, MN 55905, USA
| | - Alexander E Urban
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA.,Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.,Tashia and John Morgridge Faculty Scholar, Stanford Child Health Research Institute, Stanford, CA 94305, USA
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Proteomic analysis of the secretome of HepG2 cells indicates differential proteolytic processing after infection with dengue virus. J Proteomics 2016; 151:106-113. [PMID: 27427332 DOI: 10.1016/j.jprot.2016.07.011] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2016] [Revised: 06/27/2016] [Accepted: 07/13/2016] [Indexed: 01/04/2023]
Abstract
Secretome analysis can be described as a subset of proteomics studies consisting in the analysis of the molecules secreted by cells or tissues. Dengue virus (DENV) infection can lead to a broad spectrum of clinical manifestations, with the severe forms of the disease characterized by hemostasis abnormalities and liver injury. The hepatocytes are a relevant site of viral replication and a major source of plasma proteins. Until now, we had limited information on the small molecules secreted by hepatic cells after infection by DENV. In the present study, we analysed a fraction of the secretome of mock- and DENV-infected hepatic cells (HepG2 cells) containing molecules with <10kDa, using different proteomic approaches. We identified 175 proteins, with 57 detected only in the samples from mock-infected cells, 59 only in samples from DENV-infected cells, and 59 in both conditions. Most of the peptides identified were derived from proteins larger than 10kDa, suggesting a proteolytic processing of the secreted molecules. Using in silico analysis, we predicted consistent differences between the proteolytic processing occurring in mock and DENV-infected samples, raising, for the first time, the hypothesis that differential proteolysis of secreted molecules would be involved in the pathogenesis of dengue. BIOLOGICAL SIGNIFICANCE Since the liver, one of the targets of DENV infection, is responsible for producing molecules involved in distinct biological processes, the identification of proteins and peptides secreted by hepatocytes after infection would help to a better understanding of the physiopathology of dengue. Proteomic analyses of molecules with <10kDa secreted by HepG2 cells after infection with DENV revealed differential proteolytic processing as an effect of DENV infection.
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Schmudlach A, Felton J, Cipolla C, Sun L, Kennedy RT, Dovichi NJ. Sample preparation protocol for bottom-up proteomic analysis of the secretome of the islets of Langerhans. Analyst 2016; 141:1700-6. [PMID: 26863548 PMCID: PMC4764456 DOI: 10.1039/c5an02265g] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
We evaluate a set of protocols for preparation of the secretome from murine islets of Langerhans for bottom-up proteomic analysis. Of the protocols evaluated, a filter-aided sample preparation based approach using sodium dodecyl sulfate as a detergent to solubilize proteins generated the most protein identifications. A total of 362 protein groups (average of 3.7 peptides/protein) were identified from the secretome using the SDS-FASP protocol; a combination of data from three protocols generated 413 protein group identifications. As expected, the identified proteins included insulin 1 and 2, somatostatin, and glucagon, the four main secreted components from islets. STRING network analysis classified the other proteins as being associated with extracellular exosomes, membrane-bounded vesicles, vesicles, and the extracellular region.
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Affiliation(s)
- Andrew Schmudlach
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, USA.
| | - Jeremy Felton
- Departments of Chemistry and Pharmacology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Cynthia Cipolla
- Departments of Chemistry and Pharmacology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Liangliang Sun
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, USA.
| | - Robert T Kennedy
- Departments of Chemistry and Pharmacology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Norman J Dovichi
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, USA.
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Poirier S, Mamarbachi M, Chen WT, Lee AS, Mayer G. GRP94 Regulates Circulating Cholesterol Levels through Blockade of PCSK9-Induced LDLR Degradation. Cell Rep 2015; 13:2064-71. [PMID: 26628375 DOI: 10.1016/j.celrep.2015.11.006] [Citation(s) in RCA: 53] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2015] [Revised: 10/12/2015] [Accepted: 10/31/2015] [Indexed: 11/15/2022] Open
Abstract
Clearance of circulating low-density lipoprotein cholesterol (LDLc) by hepatic LDL receptors (LDLR) is central for vascular health. Secreted by hepatocytes, PCSK9 induces the degradation of LDLR, resulting in higher plasma LDLc levels. Still, it remains unknown why LDLR and PCSK9 co-exist within the secretory pathway of hepatocytes without leading to complete degradation of LDLR. Herein, we identified the ER-resident GRP94, and more precisely its client-binding C-terminal domain, as a PCSK9-LDLR inhibitory binding protein. Depletion of GRP94 did not affect calcium homeostasis, induce ER stress, nor did it alter PCSK9 processing or its secretion but greatly increased its capacity to induce LDLR degradation. Accordingly, we found that hepatocyte-specific Grp94-deficient mice have higher plasma LDLc levels correlated with ∼ 80% reduction in hepatic LDLR protein levels. Thus, we provide evidence that, in physiological conditions, binding of PCSK9 to GRP94 protects LDLR from degradation likely by preventing early binding of PCSK9 to LDLR within the ER.
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Affiliation(s)
- Steve Poirier
- Laboratory of Molecular Cell Biology, Montreal Heart Institute, Montréal, QC H1T 1C8, Canada; Department of Pharmacology, Faculty of Medicine, Université de Montréal, Montréal, QC H3C 3J7, Canada
| | - Maya Mamarbachi
- Laboratory of Molecular Cell Biology, Montreal Heart Institute, Montréal, QC H1T 1C8, Canada
| | - Wan-Ting Chen
- Department of Biochemistry and Molecular Biology, Keck School of Medicine, USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90089-9176, USA
| | - Amy S Lee
- Department of Biochemistry and Molecular Biology, Keck School of Medicine, USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90089-9176, USA
| | - Gaetan Mayer
- Laboratory of Molecular Cell Biology, Montreal Heart Institute, Montréal, QC H1T 1C8, Canada; Department of Pharmacology, Faculty of Medicine, Université de Montréal, Montréal, QC H3C 3J7, Canada; Department of Medicine, Faculty of Medicine, Université de Montréal, Montréal, QC H3C 3J7, Canada.
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